INFO 4940/5940: Applied Machine Learning: Methods and Applications

This page contains an outline of the topics, content, and assignments for the semester. Note that this schedule will be updated as the semester progresses and the timeline of topics and assignments might be updated throughout the semester.

week	dow	date	what	topic	prepare	slides	ae	ae_sa	hw	hw_sa	project	notes
1	Tue	Aug 27	Lec 1	Welcome to INFO 4940/5940
	Thu	Aug 29	Lec 2	Case study in ML: Property assessment in Cook County
2	Tue	Sep 3	Lec 3	Data budget/making a model
	Thu	Sep 5	Lec 4	Evaluating/tuning models
3	Tue	Sep 10		Catch-up
	Thu	Sep 12	Lec 5	Feature engineering for categorical predictors								hw-01
4	Tue	Sep 17	Lec 6	Feature engineering for numeric predictors and nonlinear relationships
	Thu	Sep 19	Lec 7	Tuning and finalizing models
5	Tue	Sep 24	Lec 8	Identifying and collecting data
	Thu	Sep 26	Lec 9	Exploratory analysis
6	Tue	Oct 1	Lec 10	Data preparation								hw-02
	Thu	Oct 3	Lec 11	Dimensionality reduction
7	Tue	Oct 8	Lec 12	Feature selection/reduction
	Thu	Oct 10	Lec 13	Fairness in machine learning
8	Tue	Oct 15		No class (Fall Break)
	Thu	Oct 17	Lec 14	Structuring the unstructured: Utilizing text for supervised models
9	Tue	Oct 22	Lec 15	An introduction to deep learning (with applications to text classification)
	Thu	Oct 24		Catch-up + project time								hw-03
10	Tue	Oct 29	Lec 16	An introduction to LLMs
	Thu	Oct 31		Prompt engineering + document labeling with LLMs
11	Tue	Nov 5	Lec 17	Explaining models through agnostic approaches
	Thu	Nov 7	Lec 18	So you've built a model: Now what?								hw-04
12	Tue	Nov 12	Lec 19	Documenting models
	Thu	Nov 14	Lec 20	Versioning and deploying models
13	Tue	Nov 19	Lec 21	More about APIs and Docker
	Thu	Nov 21	Lec 22	Catch-up
14	Tue	Nov 26	Lec 23	Group project (office hours)
	Thu	Nov 28		No class (Thanksgiving Break)
15	Tue	Dec 3	Lec 24	Monitoring model performance
	Thu	Dec 5	Lec 25	TBD